Overview

Dataset statistics

Number of variables20
Number of observations4803
Missing cells3941
Missing cells (%)4.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory750.6 KiB
Average record size in memory160.0 B

Variable types

Numeric7
Text10
Categorical2
DateTime1

Alerts

budget is highly overall correlated with popularity and 2 other fieldsHigh correlation
popularity is highly overall correlated with budget and 2 other fieldsHigh correlation
revenue is highly overall correlated with budget and 2 other fieldsHigh correlation
vote_count is highly overall correlated with budget and 2 other fieldsHigh correlation
original_language is highly imbalanced (88.8%)Imbalance
status is highly imbalanced (98.8%)Imbalance
homepage has 3091 (64.4%) missing valuesMissing
tagline has 844 (17.6%) missing valuesMissing
id has unique valuesUnique
budget has 1037 (21.6%) zerosZeros
revenue has 1427 (29.7%) zerosZeros
vote_average has 63 (1.3%) zerosZeros
vote_count has 62 (1.3%) zerosZeros

Reproduction

Analysis started2025-01-08 13:09:07.517582
Analysis finished2025-01-08 13:09:15.288288
Duration7.77 seconds
Software versionydata-profiling vv4.4.0
Download configurationconfig.json

Variables

budget
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct436
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29045040
Minimum0
Maximum3.8 × 108
Zeros1037
Zeros (%)21.6%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:15.346753image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1790000
median15000000
Q340000000
95-th percentile1.15 × 108
Maximum3.8 × 108
Range3.8 × 108
Interquartile range (IQR)39210000

Descriptive statistics

Standard deviation40722391
Coefficient of variation (CV)1.4020429
Kurtosis7.6580602
Mean29045040
Median Absolute Deviation (MAD)15000000
Skewness2.437211
Sum1.3950333 × 1011
Variance1.6583131 × 1015
MonotonicityNot monotonic
2025-01-08T13:09:15.482376image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1037
 
21.6%
20000000 144
 
3.0%
30000000 128
 
2.7%
25000000 126
 
2.6%
40000000 123
 
2.6%
15000000 120
 
2.5%
35000000 102
 
2.1%
50000000 101
 
2.1%
10000000 101
 
2.1%
60000000 86
 
1.8%
Other values (426) 2735
56.9%
ValueCountFrequency (%)
0 1037
21.6%
1 7
 
0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
10 3
 
0.1%
11 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
380000000 1
 
< 0.1%
300000000 1
 
< 0.1%
280000000 1
 
< 0.1%
270000000 1
 
< 0.1%
260000000 2
 
< 0.1%
258000000 1
 
< 0.1%
255000000 1
 
< 0.1%
250000000 8
0.2%
245000000 1
 
< 0.1%
237000000 1
 
< 0.1%

genres
Text

Distinct1175
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:15.715096image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length230
Median length194
Mean length79.281907
Min length2

Characters and Unicode

Total characters380791
Distinct characters46
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique739 ?
Unique (%)15.4%

Sample

1st row[{"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}, {"id": 14, "name": "Fantasy"}, {"id": 878, "name": "Science Fiction"}]
2nd row[{"id": 12, "name": "Adventure"}, {"id": 14, "name": "Fantasy"}, {"id": 28, "name": "Action"}]
3rd row[{"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}, {"id": 80, "name": "Crime"}]
4th row[{"id": 28, "name": "Action"}, {"id": 80, "name": "Crime"}, {"id": 18, "name": "Drama"}, {"id": 53, "name": "Thriller"}]
5th row[{"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}, {"id": 878, "name": "Science Fiction"}]
ValueCountFrequency (%)
id 12160
24.7%
name 12160
24.7%
18 2297
 
4.7%
drama 2297
 
4.7%
35 1722
 
3.5%
comedy 1722
 
3.5%
thriller 1274
 
2.6%
53 1274
 
2.6%
28 1154
 
2.3%
action 1154
 
2.3%
Other values (35) 11997
24.4%
2025-01-08T13:09:16.029596image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 72960
19.2%
44408
 
11.7%
: 24320
 
6.4%
e 20060
 
5.3%
, 19545
 
5.1%
a 19497
 
5.1%
m 18626
 
4.9%
i 18294
 
4.8%
n 17186
 
4.5%
d 14672
 
3.9%
Other values (36) 111223
29.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 142036
37.3%
Other Punctuation 116825
30.7%
Space Separator 44408
 
11.7%
Decimal Number 30885
 
8.1%
Open Punctuation 16963
 
4.5%
Close Punctuation 16963
 
4.5%
Uppercase Letter 12711
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 20060
14.1%
a 19497
13.7%
m 18626
13.1%
i 18294
12.9%
n 17186
12.1%
d 14672
10.3%
r 8803
6.2%
o 5926
 
4.2%
c 3948
 
2.8%
t 3874
 
2.7%
Other values (7) 11150
7.9%
Uppercase Letter
ValueCountFrequency (%)
C 2418
19.0%
D 2407
18.9%
A 2178
17.1%
F 1506
11.8%
T 1282
10.1%
R 894
 
7.0%
H 716
 
5.6%
M 541
 
4.3%
S 535
 
4.2%
W 226
 
1.8%
Decimal Number
ValueCountFrequency (%)
1 6036
19.5%
8 5565
18.0%
5 3653
11.8%
3 3275
10.6%
2 2792
9.0%
7 2737
8.9%
0 2667
8.6%
4 1851
 
6.0%
9 1496
 
4.8%
6 813
 
2.6%
Other Punctuation
ValueCountFrequency (%)
" 72960
62.5%
: 24320
 
20.8%
, 19545
 
16.7%
Open Punctuation
ValueCountFrequency (%)
{ 12160
71.7%
[ 4803
 
28.3%
Close Punctuation
ValueCountFrequency (%)
} 12160
71.7%
] 4803
 
28.3%
Space Separator
ValueCountFrequency (%)
44408
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 226044
59.4%
Latin 154747
40.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 20060
13.0%
a 19497
12.6%
m 18626
12.0%
i 18294
11.8%
n 17186
11.1%
d 14672
9.5%
r 8803
 
5.7%
o 5926
 
3.8%
c 3948
 
2.6%
t 3874
 
2.5%
Other values (18) 23861
15.4%
Common
ValueCountFrequency (%)
" 72960
32.3%
44408
19.6%
: 24320
 
10.8%
, 19545
 
8.6%
{ 12160
 
5.4%
} 12160
 
5.4%
1 6036
 
2.7%
8 5565
 
2.5%
] 4803
 
2.1%
[ 4803
 
2.1%
Other values (8) 19284
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 380791
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 72960
19.2%
44408
 
11.7%
: 24320
 
6.4%
e 20060
 
5.3%
, 19545
 
5.1%
a 19497
 
5.1%
m 18626
 
4.9%
i 18294
 
4.8%
n 17186
 
4.5%
d 14672
 
3.9%
Other values (36) 111223
29.2%

homepage
Text

MISSING 

Distinct1691
Distinct (%)98.8%
Missing3091
Missing (%)64.4%
Memory size37.6 KiB
2025-01-08T13:09:16.219978image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length138
Median length80
Mean length36.419977
Min length17

Characters and Unicode

Total characters62351
Distinct characters78
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1677 ?
Unique (%)98.0%

Sample

1st rowhttp://www.avatarmovie.com/
2nd rowhttp://disney.go.com/disneypictures/pirates/
3rd rowhttp://www.sonypictures.com/movies/spectre/
4th rowhttp://www.thedarkknightrises.com/
5th rowhttp://movies.disney.com/john-carter
ValueCountFrequency (%)
http://www.missionimpossible.com 5
 
0.3%
http://www.transformersmovie.com 4
 
0.2%
http://www.thehungergames.movie 4
 
0.2%
http://www.thehobbit.com 3
 
0.2%
http://www.kungfupanda.com 3
 
0.2%
http://www.lordoftherings.net 3
 
0.2%
http://disney.go.com/disneypictures/pirates 2
 
0.1%
http://www.teenagemutantninjaturtlesmovie.com 2
 
0.1%
http://www.atlasshruggedmovie.com 2
 
0.1%
http://www.twilightthemovie.com 2
 
0.1%
Other values (1675) 1683
98.2%
2025-01-08T13:09:16.570503image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 5707
 
9.2%
/ 5701
 
9.1%
e 4467
 
7.2%
o 4438
 
7.1%
w 4418
 
7.1%
m 3492
 
5.6%
. 3393
 
5.4%
h 3110
 
5.0%
i 3017
 
4.8%
c 2543
 
4.1%
Other values (68) 22065
35.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 49986
80.2%
Other Punctuation 10851
 
17.4%
Dash Punctuation 613
 
1.0%
Decimal Number 557
 
0.9%
Uppercase Letter 245
 
0.4%
Connector Punctuation 68
 
0.1%
Math Symbol 22
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 5707
11.4%
e 4467
 
8.9%
o 4438
 
8.9%
w 4418
 
8.8%
m 3492
 
7.0%
h 3110
 
6.2%
i 3017
 
6.0%
c 2543
 
5.1%
p 2347
 
4.7%
s 2280
 
4.6%
Other values (16) 14167
28.3%
Uppercase Letter
ValueCountFrequency (%)
D 22
 
9.0%
T 20
 
8.2%
A 20
 
8.2%
M 19
 
7.8%
S 17
 
6.9%
E 14
 
5.7%
L 13
 
5.3%
G 12
 
4.9%
H 10
 
4.1%
W 10
 
4.1%
Other values (15) 88
35.9%
Decimal Number
ValueCountFrequency (%)
2 104
18.7%
1 87
15.6%
0 84
15.1%
3 71
12.7%
9 44
7.9%
5 35
 
6.3%
4 34
 
6.1%
7 33
 
5.9%
6 33
 
5.9%
8 32
 
5.7%
Other Punctuation
ValueCountFrequency (%)
/ 5701
52.5%
. 3393
31.3%
: 1713
 
15.8%
# 18
 
0.2%
? 18
 
0.2%
& 3
 
< 0.1%
% 3
 
< 0.1%
, 1
 
< 0.1%
! 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 3
75.0%
} 1
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 3
75.0%
{ 1
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 613
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 68
100.0%
Math Symbol
ValueCountFrequency (%)
= 22
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 50231
80.6%
Common 12120
 
19.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 5707
 
11.4%
e 4467
 
8.9%
o 4438
 
8.8%
w 4418
 
8.8%
m 3492
 
7.0%
h 3110
 
6.2%
i 3017
 
6.0%
c 2543
 
5.1%
p 2347
 
4.7%
s 2280
 
4.5%
Other values (41) 14412
28.7%
Common
ValueCountFrequency (%)
/ 5701
47.0%
. 3393
28.0%
: 1713
 
14.1%
- 613
 
5.1%
2 104
 
0.9%
1 87
 
0.7%
0 84
 
0.7%
3 71
 
0.6%
_ 68
 
0.6%
9 44
 
0.4%
Other values (17) 242
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62351
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 5707
 
9.2%
/ 5701
 
9.1%
e 4467
 
7.2%
o 4438
 
7.1%
w 4418
 
7.1%
m 3492
 
5.6%
. 3393
 
5.4%
h 3110
 
5.0%
i 3017
 
4.8%
c 2543
 
4.1%
Other values (68) 22065
35.4%

id
Real number (ℝ)

UNIQUE 

Distinct4803
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57165.484
Minimum5
Maximum459488
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:16.679216image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile578.1
Q19014.5
median14629
Q358610.5
95-th percentile285779
Maximum459488
Range459483
Interquartile range (IQR)49596

Descriptive statistics

Standard deviation88694.614
Coefficient of variation (CV)1.5515414
Kurtosis3.3467477
Mean57165.484
Median Absolute Deviation (MAD)12920
Skewness2.0720805
Sum2.7456582 × 108
Variance7.8667346 × 109
MonotonicityNot monotonic
2025-01-08T13:09:16.796000image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19995 1
 
< 0.1%
333355 1
 
< 0.1%
71157 1
 
< 0.1%
43418 1
 
< 0.1%
11588 1
 
< 0.1%
52010 1
 
< 0.1%
9671 1
 
< 0.1%
25968 1
 
< 0.1%
41248 1
 
< 0.1%
291081 1
 
< 0.1%
Other values (4793) 4793
99.8%
ValueCountFrequency (%)
5 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
22 1
< 0.1%
ValueCountFrequency (%)
459488 1
< 0.1%
447027 1
< 0.1%
433715 1
< 0.1%
426469 1
< 0.1%
426067 1
< 0.1%
417859 1
< 0.1%
408429 1
< 0.1%
407887 1
< 0.1%
402515 1
< 0.1%
396152 1
< 0.1%
Distinct4222
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:17.128200image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length3783
Median length749
Mean length277.01145
Min length2

Characters and Unicode

Total characters1330486
Distinct characters54
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4192 ?
Unique (%)87.3%

Sample

1st row[{"id": 1463, "name": "culture clash"}, {"id": 2964, "name": "future"}, {"id": 3386, "name": "space war"}, {"id": 3388, "name": "space colony"}, {"id": 3679, "name": "society"}, {"id": 3801, "name": "space travel"}, {"id": 9685, "name": "futuristic"}, {"id": 9840, "name": "romance"}, {"id": 9882, "name": "space"}, {"id": 9951, "name": "alien"}, {"id": 10148, "name": "tribe"}, {"id": 10158, "name": "alien planet"}, {"id": 10987, "name": "cgi"}, {"id": 11399, "name": "marine"}, {"id": 13065, "name": "soldier"}, {"id": 14643, "name": "battle"}, {"id": 14720, "name": "love affair"}, {"id": 165431, "name": "anti war"}, {"id": 193554, "name": "power relations"}, {"id": 206690, "name": "mind and soul"}, {"id": 209714, "name": "3d"}]
2nd row[{"id": 270, "name": "ocean"}, {"id": 726, "name": "drug abuse"}, {"id": 911, "name": "exotic island"}, {"id": 1319, "name": "east india trading company"}, {"id": 2038, "name": "love of one's life"}, {"id": 2052, "name": "traitor"}, {"id": 2580, "name": "shipwreck"}, {"id": 2660, "name": "strong woman"}, {"id": 3799, "name": "ship"}, {"id": 5740, "name": "alliance"}, {"id": 5941, "name": "calypso"}, {"id": 6155, "name": "afterlife"}, {"id": 6211, "name": "fighter"}, {"id": 12988, "name": "pirate"}, {"id": 157186, "name": "swashbuckler"}, {"id": 179430, "name": "aftercreditsstinger"}]
3rd row[{"id": 470, "name": "spy"}, {"id": 818, "name": "based on novel"}, {"id": 4289, "name": "secret agent"}, {"id": 9663, "name": "sequel"}, {"id": 14555, "name": "mi6"}, {"id": 156095, "name": "british secret service"}, {"id": 158431, "name": "united kingdom"}]
4th row[{"id": 849, "name": "dc comics"}, {"id": 853, "name": "crime fighter"}, {"id": 949, "name": "terrorist"}, {"id": 1308, "name": "secret identity"}, {"id": 1437, "name": "burglar"}, {"id": 3051, "name": "hostage drama"}, {"id": 3562, "name": "time bomb"}, {"id": 6969, "name": "gotham city"}, {"id": 7002, "name": "vigilante"}, {"id": 9665, "name": "cover-up"}, {"id": 9715, "name": "superhero"}, {"id": 9990, "name": "villainess"}, {"id": 10044, "name": "tragic hero"}, {"id": 13015, "name": "terrorism"}, {"id": 14796, "name": "destruction"}, {"id": 18933, "name": "catwoman"}, {"id": 156082, "name": "cat burglar"}, {"id": 156395, "name": "imax"}, {"id": 173272, "name": "flood"}, {"id": 179093, "name": "criminal underworld"}, {"id": 230775, "name": "batman"}]
5th row[{"id": 818, "name": "based on novel"}, {"id": 839, "name": "mars"}, {"id": 1456, "name": "medallion"}, {"id": 3801, "name": "space travel"}, {"id": 7376, "name": "princess"}, {"id": 9951, "name": "alien"}, {"id": 10028, "name": "steampunk"}, {"id": 10539, "name": "martian"}, {"id": 10685, "name": "escape"}, {"id": 161511, "name": "edgar rice burroughs"}, {"id": 163252, "name": "alien race"}, {"id": 179102, "name": "superhuman strength"}, {"id": 190320, "name": "mars civilization"}, {"id": 195446, "name": "sword and planet"}, {"id": 207928, "name": "19th century"}, {"id": 209714, "name": "3d"}]
ValueCountFrequency (%)
id 36196
22.1%
name 36195
22.1%
of 574
 
0.4%
on 565
 
0.3%
relationship 493
 
0.3%
based 486
 
0.3%
film 430
 
0.3%
429
 
0.3%
woman 413
 
0.3%
love 361
 
0.2%
Other values (17077) 87393
53.4%
2025-01-08T13:09:17.603563image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 217168
16.3%
158748
 
11.9%
e 74082
 
5.6%
: 72388
 
5.4%
, 68006
 
5.1%
i 66211
 
5.0%
a 65403
 
4.9%
n 61324
 
4.6%
d 49281
 
3.7%
m 47096
 
3.5%
Other values (44) 450779
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 564664
42.4%
Other Punctuation 358011
26.9%
Decimal Number 166577
 
12.5%
Space Separator 158748
 
11.9%
Open Punctuation 41020
 
3.1%
Close Punctuation 41020
 
3.1%
Dash Punctuation 445
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 74082
13.1%
i 66211
11.7%
a 65403
11.6%
n 61324
10.9%
d 49281
8.7%
m 47096
8.3%
r 28253
 
5.0%
o 24680
 
4.4%
t 23991
 
4.2%
s 22454
 
4.0%
Other values (16) 101889
18.0%
Decimal Number
ValueCountFrequency (%)
1 30214
18.1%
2 16715
10.0%
3 16544
9.9%
0 15763
9.5%
5 15519
9.3%
6 15478
9.3%
4 14723
8.8%
9 14101
8.5%
7 13773
8.3%
8 13747
8.3%
Other Punctuation
ValueCountFrequency (%)
" 217168
60.7%
: 72388
 
20.2%
, 68006
 
19.0%
. 182
 
0.1%
' 171
 
< 0.1%
\ 91
 
< 0.1%
& 2
 
< 0.1%
/ 2
 
< 0.1%
* 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
{ 36194
88.2%
[ 4803
 
11.7%
( 23
 
0.1%
Close Punctuation
ValueCountFrequency (%)
} 36194
88.2%
] 4803
 
11.7%
) 23
 
0.1%
Space Separator
ValueCountFrequency (%)
158748
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 445
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 765822
57.6%
Latin 564664
42.4%

Most frequent character per script

Common
ValueCountFrequency (%)
" 217168
28.4%
158748
20.7%
: 72388
 
9.5%
, 68006
 
8.9%
{ 36194
 
4.7%
} 36194
 
4.7%
1 30214
 
3.9%
2 16715
 
2.2%
3 16544
 
2.2%
0 15763
 
2.1%
Other values (18) 97888
12.8%
Latin
ValueCountFrequency (%)
e 74082
13.1%
i 66211
11.7%
a 65403
11.6%
n 61324
10.9%
d 49281
8.7%
m 47096
8.3%
r 28253
 
5.0%
o 24680
 
4.4%
t 23991
 
4.2%
s 22454
 
4.0%
Other values (16) 101889
18.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1330486
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 217168
16.3%
158748
 
11.9%
e 74082
 
5.6%
: 72388
 
5.4%
, 68006
 
5.1%
i 66211
 
5.0%
a 65403
 
4.9%
n 61324
 
4.6%
d 49281
 
3.7%
m 47096
 
3.5%
Other values (44) 450779
33.9%

original_language
Categorical

IMBALANCE 

Distinct37
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
en
4505 
fr
 
70
es
 
32
zh
 
27
de
 
27
Other values (32)
 
142

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters9606
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)0.3%

Sample

1st rowen
2nd rowen
3rd rowen
4th rowen
5th rowen

Common Values

ValueCountFrequency (%)
en 4505
93.8%
fr 70
 
1.5%
es 32
 
0.7%
zh 27
 
0.6%
de 27
 
0.6%
hi 19
 
0.4%
ja 16
 
0.3%
it 14
 
0.3%
cn 12
 
0.2%
ko 11
 
0.2%
Other values (27) 70
 
1.5%

Length

2025-01-08T13:09:17.708805image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
en 4505
93.8%
fr 70
 
1.5%
es 32
 
0.7%
zh 27
 
0.6%
de 27
 
0.6%
hi 19
 
0.4%
ja 16
 
0.3%
it 14
 
0.3%
cn 12
 
0.2%
ru 11
 
0.2%
Other values (27) 70
 
1.5%

Most occurring characters

ValueCountFrequency (%)
e 4569
47.6%
n 4523
47.1%
r 86
 
0.9%
f 75
 
0.8%
h 53
 
0.6%
s 42
 
0.4%
i 37
 
0.4%
d 36
 
0.4%
a 32
 
0.3%
t 30
 
0.3%
Other values (12) 123
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9606
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4569
47.6%
n 4523
47.1%
r 86
 
0.9%
f 75
 
0.8%
h 53
 
0.6%
s 42
 
0.4%
i 37
 
0.4%
d 36
 
0.4%
a 32
 
0.3%
t 30
 
0.3%
Other values (12) 123
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 9606
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4569
47.6%
n 4523
47.1%
r 86
 
0.9%
f 75
 
0.8%
h 53
 
0.6%
s 42
 
0.4%
i 37
 
0.4%
d 36
 
0.4%
a 32
 
0.3%
t 30
 
0.3%
Other values (12) 123
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9606
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4569
47.6%
n 4523
47.1%
r 86
 
0.9%
f 75
 
0.8%
h 53
 
0.6%
s 42
 
0.4%
i 37
 
0.4%
d 36
 
0.4%
a 32
 
0.3%
t 30
 
0.3%
Other values (12) 123
 
1.3%
Distinct4801
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:17.982506image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length86
Median length59
Mean length15.222986
Min length1

Characters and Unicode

Total characters73116
Distinct characters410
Distinct categories19 ?
Distinct scripts13 ?
Distinct blocks14 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4799 ?
Unique (%)99.9%

Sample

1st rowAvatar
2nd rowPirates of the Caribbean: At World's End
3rd rowSpectre
4th rowThe Dark Knight Rises
5th rowJohn Carter
ValueCountFrequency (%)
the 1420
 
10.7%
of 432
 
3.3%
a 168
 
1.3%
and 127
 
1.0%
in 110
 
0.8%
2 102
 
0.8%
to 102
 
0.8%
80
 
0.6%
man 65
 
0.5%
love 53
 
0.4%
Other values (5055) 10578
79.9%
2025-01-08T13:09:18.407768image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8436
 
11.5%
e 7412
 
10.1%
a 4625
 
6.3%
o 4370
 
6.0%
r 3892
 
5.3%
n 3885
 
5.3%
i 3723
 
5.1%
t 3600
 
4.9%
s 2857
 
3.9%
h 2717
 
3.7%
Other values (400) 27599
37.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51401
70.3%
Uppercase Letter 11413
 
15.6%
Space Separator 8436
 
11.5%
Other Punctuation 906
 
1.2%
Decimal Number 494
 
0.7%
Other Letter 328
 
0.4%
Dash Punctuation 84
 
0.1%
Spacing Mark 16
 
< 0.1%
Nonspacing Mark 8
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Other values (9) 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ا 7
 
2.1%
7
 
2.1%
ی 6
 
1.8%
5
 
1.5%
4
 
1.2%
4
 
1.2%
4
 
1.2%
ن 4
 
1.2%
3
 
0.9%
د 3
 
0.9%
Other values (229) 281
85.7%
Lowercase Letter
ValueCountFrequency (%)
e 7412
14.4%
a 4625
 
9.0%
o 4370
 
8.5%
r 3892
 
7.6%
n 3885
 
7.6%
i 3723
 
7.2%
t 3600
 
7.0%
s 2857
 
5.6%
h 2717
 
5.3%
l 2426
 
4.7%
Other values (70) 11894
23.1%
Uppercase Letter
ValueCountFrequency (%)
T 1562
13.7%
S 972
 
8.5%
M 777
 
6.8%
B 733
 
6.4%
D 680
 
6.0%
C 638
 
5.6%
A 618
 
5.4%
L 565
 
5.0%
H 526
 
4.6%
P 470
 
4.1%
Other values (27) 3872
33.9%
Other Punctuation
ValueCountFrequency (%)
: 341
37.6%
' 222
24.5%
. 141
15.6%
, 75
 
8.3%
& 60
 
6.6%
! 35
 
3.9%
? 18
 
2.0%
/ 7
 
0.8%
# 2
 
0.2%
* 2
 
0.2%
Other values (3) 3
 
0.3%
Decimal Number
ValueCountFrequency (%)
2 144
29.1%
1 78
15.8%
3 74
15.0%
0 74
15.0%
4 35
 
7.1%
5 21
 
4.3%
8 21
 
4.3%
9 17
 
3.4%
7 15
 
3.0%
6 15
 
3.0%
Spacing Mark
ValueCountFrequency (%)
5
31.2%
3
18.8%
3
18.8%
2
 
12.5%
ि 2
 
12.5%
1
 
6.2%
Nonspacing Mark
ValueCountFrequency (%)
2
25.0%
2
25.0%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Other Number
ValueCountFrequency (%)
³ 1
25.0%
½ 1
25.0%
² 1
25.0%
1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
97.6%
2
 
2.4%
Close Punctuation
ValueCountFrequency (%)
) 4
66.7%
] 2
33.3%
Open Punctuation
ValueCountFrequency (%)
( 4
66.7%
[ 2
33.3%
Currency Symbol
ValueCountFrequency (%)
$ 3
60.0%
¢ 2
40.0%
Space Separator
ValueCountFrequency (%)
8436
100.0%
Final Punctuation
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Format
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 62677
85.7%
Common 9949
 
13.6%
Han 160
 
0.2%
Cyrillic 127
 
0.2%
Hangul 45
 
0.1%
Arabic 39
 
0.1%
Devanagari 35
 
< 0.1%
Katakana 26
 
< 0.1%
Hiragana 17
 
< 0.1%
Thai 17
 
< 0.1%
Other values (3) 24
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
5
 
3.1%
4
 
2.5%
4
 
2.5%
3
 
1.9%
3
 
1.9%
3
 
1.9%
2
 
1.2%
2
 
1.2%
2
 
1.2%
2
 
1.2%
Other values (113) 130
81.2%
Latin
ValueCountFrequency (%)
e 7412
 
11.8%
a 4625
 
7.4%
o 4370
 
7.0%
r 3892
 
6.2%
n 3885
 
6.2%
i 3723
 
5.9%
t 3600
 
5.7%
s 2857
 
4.6%
h 2717
 
4.3%
l 2426
 
3.9%
Other values (62) 23170
37.0%
Common
ValueCountFrequency (%)
8436
84.8%
: 341
 
3.4%
' 222
 
2.2%
2 144
 
1.4%
. 141
 
1.4%
- 82
 
0.8%
1 78
 
0.8%
, 75
 
0.8%
3 74
 
0.7%
0 74
 
0.7%
Other values (31) 282
 
2.8%
Hangul
ValueCountFrequency (%)
3
 
6.7%
2
 
4.4%
2
 
4.4%
2
 
4.4%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
Other values (30) 30
66.7%
Cyrillic
ValueCountFrequency (%)
о 18
14.2%
е 10
 
7.9%
а 10
 
7.9%
р 9
 
7.1%
н 8
 
6.3%
л 7
 
5.5%
в 6
 
4.7%
и 6
 
4.7%
С 5
 
3.9%
б 4
 
3.1%
Other values (26) 44
34.6%
Devanagari
ValueCountFrequency (%)
5
14.3%
4
 
11.4%
3
 
8.6%
2
 
5.7%
2
 
5.7%
ि 2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
Other values (10) 10
28.6%
Katakana
ValueCountFrequency (%)
3
 
11.5%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (10) 10
38.5%
Arabic
ValueCountFrequency (%)
ا 7
17.9%
ی 6
15.4%
ن 4
10.3%
د 3
7.7%
ر 3
7.7%
س 3
7.7%
ه 3
7.7%
م 2
 
5.1%
ب 2
 
5.1%
آ 1
 
2.6%
Other values (5) 5
12.8%
Thai
ValueCountFrequency (%)
2
11.8%
2
11.8%
2
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (4) 4
23.5%
Hiragana
ValueCountFrequency (%)
7
41.2%
2
 
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Tamil
ValueCountFrequency (%)
3
23.1%
2
15.4%
2
15.4%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Greek
ValueCountFrequency (%)
ν 2
20.0%
Κ 1
10.0%
υ 1
10.0%
ό 1
10.0%
δ 1
10.0%
ο 1
10.0%
τ 1
10.0%
α 1
10.0%
ς 1
10.0%
Inherited
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72554
99.2%
CJK 160
 
0.2%
Cyrillic 127
 
0.2%
None 72
 
0.1%
Hangul 45
 
0.1%
Arabic 39
 
0.1%
Devanagari 35
 
< 0.1%
Katakana 28
 
< 0.1%
Hiragana 17
 
< 0.1%
Thai 17
 
< 0.1%
Other values (4) 22
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8436
 
11.6%
e 7412
 
10.2%
a 4625
 
6.4%
o 4370
 
6.0%
r 3892
 
5.4%
n 3885
 
5.4%
i 3723
 
5.1%
t 3600
 
5.0%
s 2857
 
3.9%
h 2717
 
3.7%
Other values (71) 27037
37.3%
None
ValueCountFrequency (%)
é 18
25.0%
à 4
 
5.6%
ó 4
 
5.6%
è 4
 
5.6%
á 3
 
4.2%
å 3
 
4.2%
í 3
 
4.2%
ñ 2
 
2.8%
ø 2
 
2.8%
ă 2
 
2.8%
Other values (24) 27
37.5%
Cyrillic
ValueCountFrequency (%)
о 18
14.2%
е 10
 
7.9%
а 10
 
7.9%
р 9
 
7.1%
н 8
 
6.3%
л 7
 
5.5%
в 6
 
4.7%
и 6
 
4.7%
С 5
 
3.9%
б 4
 
3.1%
Other values (26) 44
34.6%
Arabic
ValueCountFrequency (%)
ا 7
17.9%
ی 6
15.4%
ن 4
10.3%
د 3
7.7%
ر 3
7.7%
س 3
7.7%
ه 3
7.7%
م 2
 
5.1%
ب 2
 
5.1%
آ 1
 
2.6%
Other values (5) 5
12.8%
Hiragana
ValueCountFrequency (%)
7
41.2%
2
 
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
CJK
ValueCountFrequency (%)
5
 
3.1%
4
 
2.5%
4
 
2.5%
3
 
1.9%
3
 
1.9%
3
 
1.9%
2
 
1.2%
2
 
1.2%
2
 
1.2%
2
 
1.2%
Other values (113) 130
81.2%
Devanagari
ValueCountFrequency (%)
5
14.3%
4
 
11.4%
3
 
8.6%
2
 
5.7%
2
 
5.7%
ि 2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
Other values (10) 10
28.6%
Punctuation
ValueCountFrequency (%)
3
42.9%
2
28.6%
1
 
14.3%
1
 
14.3%
Tamil
ValueCountFrequency (%)
3
23.1%
2
15.4%
2
15.4%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Hangul
ValueCountFrequency (%)
3
 
6.7%
2
 
4.4%
2
 
4.4%
2
 
4.4%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
Other values (30) 30
66.7%
Katakana
ValueCountFrequency (%)
3
 
10.7%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
1
 
3.6%
1
 
3.6%
1
 
3.6%
1
 
3.6%
1
 
3.6%
Other values (12) 12
42.9%
Thai
ValueCountFrequency (%)
2
11.8%
2
11.8%
2
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (4) 4
23.5%
Latin Ext Additional
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct4800
Distinct (%)100.0%
Missing3
Missing (%)0.1%
Memory size37.6 KiB
2025-01-08T13:09:18.691695image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length1000
Median length625
Mean length305.39875
Min length1

Characters and Unicode

Total characters1465914
Distinct characters127
Distinct categories19 ?
Distinct scripts2 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4800 ?
Unique (%)100.0%

Sample

1st rowIn the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.
2nd rowCaptain Barbossa, long believed to be dead, has come back to life and is headed to the edge of the Earth with Will Turner and Elizabeth Swann. But nothing is quite as it seems.
3rd rowA cryptic message from Bond’s past sends him on a trail to uncover a sinister organization. While M battles political forces to keep the secret service alive, Bond peels back the layers of deceit to reveal the terrible truth behind SPECTRE.
4th rowFollowing the death of District Attorney Harvey Dent, Batman assumes responsibility for Dent's crimes to protect the late attorney's reputation and is subsequently hunted by the Gotham City Police Department. Eight years later, Batman encounters the mysterious Selina Kyle and the villainous Bane, a new terrorist leader who overwhelms Gotham's finest. The Dark Knight resurfaces to protect a city that has branded him an enemy.
5th rowJohn Carter is a war-weary, former military captain who's inexplicably transported to the mysterious and exotic planet of Barsoom (Mars) and reluctantly becomes embroiled in an epic conflict. It's a world on the brink of collapse, and Carter rediscovers his humanity when he realizes the survival of Barsoom and its people rests in his hands.
ValueCountFrequency (%)
the 13894
 
5.5%
a 10452
 
4.2%
to 7925
 
3.2%
and 7388
 
3.0%
of 6867
 
2.7%
in 4536
 
1.8%
his 3994
 
1.6%
is 3369
 
1.3%
with 2533
 
1.0%
her 2163
 
0.9%
Other values (24224) 187234
74.8%
2025-01-08T13:09:19.090845image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
245712
16.8%
e 141178
 
9.6%
t 97104
 
6.6%
a 94907
 
6.5%
i 85329
 
5.8%
o 84373
 
5.8%
n 84015
 
5.7%
s 78343
 
5.3%
r 77154
 
5.3%
h 61948
 
4.2%
Other values (117) 415851
28.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1139845
77.8%
Space Separator 245716
 
16.8%
Uppercase Letter 39039
 
2.7%
Other Punctuation 30988
 
2.1%
Dash Punctuation 4474
 
0.3%
Decimal Number 3915
 
0.3%
Open Punctuation 757
 
0.1%
Close Punctuation 754
 
0.1%
Final Punctuation 310
 
< 0.1%
Initial Punctuation 49
 
< 0.1%
Other values (9) 67
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 141178
12.4%
t 97104
 
8.5%
a 94907
 
8.3%
i 85329
 
7.5%
o 84373
 
7.4%
n 84015
 
7.4%
s 78343
 
6.9%
r 77154
 
6.8%
h 61948
 
5.4%
l 48681
 
4.3%
Other values (36) 286813
25.2%
Uppercase Letter
ValueCountFrequency (%)
A 4448
 
11.4%
T 3268
 
8.4%
S 2934
 
7.5%
B 2671
 
6.8%
C 2467
 
6.3%
M 2307
 
5.9%
W 2098
 
5.4%
H 1808
 
4.6%
D 1682
 
4.3%
I 1604
 
4.1%
Other values (18) 13752
35.2%
Other Punctuation
ValueCountFrequency (%)
, 13388
43.2%
. 12056
38.9%
' 3577
 
11.5%
" 1021
 
3.3%
: 284
 
0.9%
? 218
 
0.7%
; 175
 
0.6%
! 142
 
0.5%
/ 57
 
0.2%
35
 
0.1%
Other values (5) 35
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 926
23.7%
0 821
21.0%
9 568
14.5%
2 371
9.5%
5 231
 
5.9%
7 224
 
5.7%
8 206
 
5.3%
3 199
 
5.1%
4 189
 
4.8%
6 180
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 4206
94.0%
205
 
4.6%
62
 
1.4%
1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 2
40.0%
1
20.0%
~ 1
20.0%
| 1
20.0%
Space Separator
ValueCountFrequency (%)
245712
> 99.9%
  4
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 755
99.7%
[ 2
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 753
99.9%
] 1
 
0.1%
Final Punctuation
ValueCountFrequency (%)
275
88.7%
35
 
11.3%
Currency Symbol
ValueCountFrequency (%)
$ 45
97.8%
£ 1
 
2.2%
Initial Punctuation
ValueCountFrequency (%)
35
71.4%
14
 
28.6%
Other Symbol
ValueCountFrequency (%)
® 3
75.0%
¦ 1
 
25.0%
Format
ValueCountFrequency (%)
­ 3
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Modifier Letter
ValueCountFrequency (%)
ʼ 1
100.0%
Other Number
ValueCountFrequency (%)
¹ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1178884
80.4%
Common 287030
 
19.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 141178
12.0%
t 97104
 
8.2%
a 94907
 
8.1%
i 85329
 
7.2%
o 84373
 
7.2%
n 84015
 
7.1%
s 78343
 
6.6%
r 77154
 
6.5%
h 61948
 
5.3%
l 48681
 
4.1%
Other values (64) 325852
27.6%
Common
ValueCountFrequency (%)
245712
85.6%
, 13388
 
4.7%
. 12056
 
4.2%
- 4206
 
1.5%
' 3577
 
1.2%
" 1021
 
0.4%
1 926
 
0.3%
0 821
 
0.3%
( 755
 
0.3%
) 753
 
0.3%
Other values (43) 3815
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1465079
99.9%
Punctuation 662
 
< 0.1%
None 170
 
< 0.1%
Modifier Letters 1
 
< 0.1%
Alphabetic PF 1
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
245712
16.8%
e 141178
 
9.6%
t 97104
 
6.6%
a 94907
 
6.5%
i 85329
 
5.8%
o 84373
 
5.8%
n 84015
 
5.7%
s 78343
 
5.3%
r 77154
 
5.3%
h 61948
 
4.2%
Other values (77) 415016
28.3%
Punctuation
ValueCountFrequency (%)
275
41.5%
205
31.0%
62
 
9.4%
35
 
5.3%
35
 
5.3%
35
 
5.3%
14
 
2.1%
1
 
0.2%
None
ValueCountFrequency (%)
é 92
54.1%
á 12
 
7.1%
ó 8
 
4.7%
è 4
 
2.4%
ö 4
 
2.4%
ç 4
 
2.4%
ï 4
 
2.4%
í 4
 
2.4%
  4
 
2.4%
ñ 3
 
1.8%
Other values (19) 31
 
18.2%
Modifier Letters
ValueCountFrequency (%)
ʼ 1
100.0%
Alphabetic PF
ValueCountFrequency (%)
1
100.0%
Math Operators
ValueCountFrequency (%)
1
100.0%

popularity
Real number (ℝ)

HIGH CORRELATION 

Distinct4802
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.492301
Minimum0
Maximum875.58131
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:19.208355image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3628167
Q14.66807
median12.921594
Q328.313505
95-th percentile67.385962
Maximum875.58131
Range875.58131
Interquartile range (IQR)23.645435

Descriptive statistics

Standard deviation31.81665
Coefficient of variation (CV)1.4803743
Kurtosis191.99582
Mean21.492301
Median Absolute Deviation (MAD)9.814445
Skewness9.7214159
Sum103227.52
Variance1012.2992
MonotonicityNot monotonic
2025-01-08T13:09:19.314068image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.902102 2
 
< 0.1%
150.437577 1
 
< 0.1%
7.247023 1
 
< 0.1%
14.038703 1
 
< 0.1%
3.949796 1
 
< 0.1%
3.789485 1
 
< 0.1%
3.891186 1
 
< 0.1%
16.072466 1
 
< 0.1%
4.799022 1
 
< 0.1%
2.351706 1
 
< 0.1%
Other values (4792) 4792
99.8%
ValueCountFrequency (%)
0 1
< 0.1%
0.000372 1
< 0.1%
0.001117 1
< 0.1%
0.001186 1
< 0.1%
0.001389 1
< 0.1%
0.001586 1
< 0.1%
0.002386 1
< 0.1%
0.002388 1
< 0.1%
0.003142 1
< 0.1%
0.003352 1
< 0.1%
ValueCountFrequency (%)
875.581305 1
< 0.1%
724.247784 1
< 0.1%
514.569956 1
< 0.1%
481.098624 1
< 0.1%
434.278564 1
< 0.1%
418.708552 1
< 0.1%
271.972889 1
< 0.1%
243.791743 1
< 0.1%
206.227151 1
< 0.1%
203.73459 1
< 0.1%
Distinct3697
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:19.625610image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length1155
Median length469
Mean length128.01499
Min length2

Characters and Unicode

Total characters614856
Distinct characters83
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3497 ?
Unique (%)72.8%

Sample

1st row[{"name": "Ingenious Film Partners", "id": 289}, {"name": "Twentieth Century Fox Film Corporation", "id": 306}, {"name": "Dune Entertainment", "id": 444}, {"name": "Lightstorm Entertainment", "id": 574}]
2nd row[{"name": "Walt Disney Pictures", "id": 2}, {"name": "Jerry Bruckheimer Films", "id": 130}, {"name": "Second Mate Productions", "id": 19936}]
3rd row[{"name": "Columbia Pictures", "id": 5}, {"name": "Danjaq", "id": 10761}, {"name": "B24", "id": 69434}]
4th row[{"name": "Legendary Pictures", "id": 923}, {"name": "Warner Bros.", "id": 6194}, {"name": "DC Entertainment", "id": 9993}, {"name": "Syncopy", "id": 9996}]
5th row[{"name": "Walt Disney Pictures", "id": 2}]
ValueCountFrequency (%)
name 13677
 
18.1%
id 13677
 
18.1%
pictures 2584
 
3.4%
films 1883
 
2.5%
productions 1830
 
2.4%
entertainment 1567
 
2.1%
film 915
 
1.2%
538
 
0.7%
corporation 404
 
0.5%
fox 372
 
0.5%
Other values (10124) 38291
50.6%
2025-01-08T13:09:20.242635image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 82064
 
13.3%
70935
 
11.5%
i 34526
 
5.6%
e 34198
 
5.6%
n 32605
 
5.3%
a 28315
 
4.6%
: 27355
 
4.4%
, 22976
 
3.7%
m 22254
 
3.6%
d 19878
 
3.2%
Other values (73) 239750
39.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 279221
45.4%
Other Punctuation 134101
21.8%
Space Separator 70935
 
11.5%
Decimal Number 54691
 
8.9%
Uppercase Letter 37429
 
6.1%
Close Punctuation 18933
 
3.1%
Open Punctuation 18933
 
3.1%
Dash Punctuation 500
 
0.1%
Math Symbol 113
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 34526
12.4%
e 34198
12.2%
n 32605
11.7%
a 28315
10.1%
m 22254
8.0%
d 19878
7.1%
t 18386
6.6%
r 17181
 
6.2%
o 15560
 
5.6%
s 12762
 
4.6%
Other values (16) 43556
15.6%
Uppercase Letter
ValueCountFrequency (%)
P 6167
16.5%
F 4436
11.9%
C 3700
 
9.9%
M 2429
 
6.5%
E 2337
 
6.2%
S 2241
 
6.0%
T 1644
 
4.4%
B 1566
 
4.2%
A 1427
 
3.8%
G 1409
 
3.8%
Other values (16) 10073
26.9%
Other Punctuation
ValueCountFrequency (%)
" 82064
61.2%
: 27355
 
20.4%
, 22976
 
17.1%
. 835
 
0.6%
\ 455
 
0.3%
/ 176
 
0.1%
& 161
 
0.1%
' 71
 
0.1%
! 4
 
< 0.1%
@ 2
 
< 0.1%
Other values (2) 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 8454
15.5%
2 6455
11.8%
3 5968
10.9%
4 5535
10.1%
0 5406
9.9%
5 4943
9.0%
6 4700
8.6%
9 4577
8.4%
7 4350
8.0%
8 4303
7.9%
Close Punctuation
ValueCountFrequency (%)
} 13677
72.2%
] 4803
 
25.4%
) 453
 
2.4%
Open Punctuation
ValueCountFrequency (%)
{ 13677
72.2%
[ 4803
 
25.4%
( 453
 
2.4%
Space Separator
ValueCountFrequency (%)
70935
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 500
100.0%
Math Symbol
ValueCountFrequency (%)
+ 113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 316650
51.5%
Common 298206
48.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 34526
10.9%
e 34198
10.8%
n 32605
10.3%
a 28315
 
8.9%
m 22254
 
7.0%
d 19878
 
6.3%
t 18386
 
5.8%
r 17181
 
5.4%
o 15560
 
4.9%
s 12762
 
4.0%
Other values (42) 80985
25.6%
Common
ValueCountFrequency (%)
" 82064
27.5%
70935
23.8%
: 27355
 
9.2%
, 22976
 
7.7%
} 13677
 
4.6%
{ 13677
 
4.6%
1 8454
 
2.8%
2 6455
 
2.2%
3 5968
 
2.0%
4 5535
 
1.9%
Other values (21) 41110
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 614856
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 82064
 
13.3%
70935
 
11.5%
i 34526
 
5.6%
e 34198
 
5.6%
n 32605
 
5.3%
a 28315
 
4.6%
: 27355
 
4.4%
, 22976
 
3.7%
m 22254
 
3.6%
d 19878
 
3.2%
Other values (73) 239750
39.0%
Distinct469
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:20.476056image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length517
Median length58
Mean length69.921299
Min length2

Characters and Unicode

Total characters335832
Distinct characters61
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique353 ?
Unique (%)7.3%

Sample

1st row[{"iso_3166_1": "US", "name": "United States of America"}, {"iso_3166_1": "GB", "name": "United Kingdom"}]
2nd row[{"iso_3166_1": "US", "name": "United States of America"}]
3rd row[{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]
4th row[{"iso_3166_1": "US", "name": "United States of America"}]
5th row[{"iso_3166_1": "US", "name": "United States of America"}]
ValueCountFrequency (%)
iso_3166_1 6436
16.7%
name 6436
16.7%
united 4606
11.9%
of 3956
10.2%
america 3956
10.2%
us 3956
10.2%
states 3956
10.2%
kingdom 636
 
1.6%
gb 636
 
1.6%
de 324
 
0.8%
Other values (180) 3698
9.6%
2025-01-08T13:09:20.830482image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 51488
 
15.3%
33793
 
10.1%
e 19992
 
6.0%
a 16820
 
5.0%
i 16187
 
4.8%
n 13165
 
3.9%
_ 12872
 
3.8%
1 12872
 
3.8%
6 12872
 
3.8%
: 12872
 
3.8%
Other values (51) 132899
39.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 133878
39.9%
Other Punctuation 72603
21.6%
Space Separator 33793
 
10.1%
Decimal Number 32180
 
9.6%
Uppercase Letter 28028
 
8.3%
Connector Punctuation 12872
 
3.8%
Open Punctuation 11239
 
3.3%
Close Punctuation 11239
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 19992
14.9%
a 16820
12.6%
i 16187
12.1%
n 13165
9.8%
t 12819
9.6%
m 11448
8.6%
o 11294
8.4%
s 10601
7.9%
d 5708
 
4.3%
r 4964
 
3.7%
Other values (15) 10880
8.1%
Uppercase Letter
ValueCountFrequency (%)
U 8717
31.1%
S 8175
29.2%
A 4550
16.2%
G 979
 
3.5%
K 802
 
2.9%
B 735
 
2.6%
C 723
 
2.6%
F 625
 
2.2%
E 511
 
1.8%
R 443
 
1.6%
Other values (14) 1768
 
6.3%
Other Punctuation
ValueCountFrequency (%)
" 51488
70.9%
: 12872
 
17.7%
, 8243
 
11.4%
Decimal Number
ValueCountFrequency (%)
1 12872
40.0%
6 12872
40.0%
3 6436
20.0%
Open Punctuation
ValueCountFrequency (%)
{ 6436
57.3%
[ 4803
42.7%
Close Punctuation
ValueCountFrequency (%)
} 6436
57.3%
] 4803
42.7%
Space Separator
ValueCountFrequency (%)
33793
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 12872
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 173926
51.8%
Latin 161906
48.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 19992
12.3%
a 16820
10.4%
i 16187
10.0%
n 13165
8.1%
t 12819
 
7.9%
m 11448
 
7.1%
o 11294
 
7.0%
s 10601
 
6.5%
U 8717
 
5.4%
S 8175
 
5.0%
Other values (39) 32688
20.2%
Common
ValueCountFrequency (%)
" 51488
29.6%
33793
19.4%
_ 12872
 
7.4%
1 12872
 
7.4%
6 12872
 
7.4%
: 12872
 
7.4%
, 8243
 
4.7%
{ 6436
 
3.7%
3 6436
 
3.7%
} 6436
 
3.7%
Other values (2) 9606
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 335832
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 51488
 
15.3%
33793
 
10.1%
e 19992
 
6.0%
a 16820
 
5.0%
i 16187
 
4.8%
n 13165
 
3.9%
_ 12872
 
3.8%
1 12872
 
3.8%
6 12872
 
3.8%
: 12872
 
3.8%
Other values (51) 132899
39.6%
Distinct3280
Distinct (%)68.3%
Missing1
Missing (%)< 0.1%
Memory size37.6 KiB
Minimum1916-09-04 00:00:00
Maximum2017-02-03 00:00:00
2025-01-08T13:09:20.937840image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:21.069563image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

revenue
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3297
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82260639
Minimum0
Maximum2.7879651 × 109
Zeros1427
Zeros (%)29.7%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:21.202031image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median19170001
Q392917187
95-th percentile3.692849 × 108
Maximum2.7879651 × 109
Range2.7879651 × 109
Interquartile range (IQR)92917187

Descriptive statistics

Standard deviation1.628571 × 108
Coefficient of variation (CV)1.9797695
Kurtosis33.12363
Mean82260639
Median Absolute Deviation (MAD)19170001
Skewness4.4447164
Sum3.9509785 × 1011
Variance2.6522435 × 1016
MonotonicityNot monotonic
2025-01-08T13:09:21.311372image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1427
29.7%
7000000 6
 
0.1%
8000000 6
 
0.1%
6000000 5
 
0.1%
12000000 5
 
0.1%
10000000 5
 
0.1%
100000000 5
 
0.1%
14000000 4
 
0.1%
11000000 4
 
0.1%
5000000 4
 
0.1%
Other values (3287) 3332
69.4%
ValueCountFrequency (%)
0 1427
29.7%
5 1
 
< 0.1%
7 2
 
< 0.1%
10 1
 
< 0.1%
11 2
 
< 0.1%
12 2
 
< 0.1%
13 1
 
< 0.1%
14 1
 
< 0.1%
15 1
 
< 0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
2787965087 1
< 0.1%
1845034188 1
< 0.1%
1519557910 1
< 0.1%
1513528810 1
< 0.1%
1506249360 1
< 0.1%
1405403694 1
< 0.1%
1274219009 1
< 0.1%
1215439994 1
< 0.1%
1156730962 1
< 0.1%
1153304495 1
< 0.1%

runtime
Real number (ℝ)

Distinct156
Distinct (%)3.2%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean106.87586
Minimum0
Maximum338
Zeros35
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:21.457367image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile83
Q194
median103
Q3118
95-th percentile144
Maximum338
Range338
Interquartile range (IQR)24

Descriptive statistics

Standard deviation22.611935
Coefficient of variation (CV)0.21157196
Kurtosis8.9354488
Mean106.87586
Median Absolute Deviation (MAD)11
Skewness0.71595651
Sum513111
Variance511.29959
MonotonicityNot monotonic
2025-01-08T13:09:21.586463image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 163
 
3.4%
100 149
 
3.1%
98 140
 
2.9%
97 133
 
2.8%
95 123
 
2.6%
99 119
 
2.5%
94 116
 
2.4%
96 115
 
2.4%
101 114
 
2.4%
93 113
 
2.4%
Other values (146) 3516
73.2%
ValueCountFrequency (%)
0 35
0.7%
14 1
 
< 0.1%
25 1
 
< 0.1%
41 1
 
< 0.1%
42 1
 
< 0.1%
46 1
 
< 0.1%
47 1
 
< 0.1%
53 1
 
< 0.1%
59 1
 
< 0.1%
60 1
 
< 0.1%
ValueCountFrequency (%)
338 1
< 0.1%
276 1
< 0.1%
254 1
< 0.1%
248 1
< 0.1%
242 1
< 0.1%
240 1
< 0.1%
238 1
< 0.1%
229 1
< 0.1%
225 1
< 0.1%
219 1
< 0.1%
Distinct544
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:21.772178image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length474
Median length40
Mean length62.923381
Min length2

Characters and Unicode

Total characters302221
Distinct characters68
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique416 ?
Unique (%)8.7%

Sample

1st row[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "es", "name": "Espa\u00f1ol"}]
2nd row[{"iso_639_1": "en", "name": "English"}]
3rd row[{"iso_639_1": "fr", "name": "Fran\u00e7ais"}, {"iso_639_1": "en", "name": "English"}, {"iso_639_1": "es", "name": "Espa\u00f1ol"}, {"iso_639_1": "it", "name": "Italiano"}, {"iso_639_1": "de", "name": "Deutsch"}]
4th row[{"iso_639_1": "en", "name": "English"}]
5th row[{"iso_639_1": "en", "name": "English"}]
ValueCountFrequency (%)
iso_639_1 6937
24.8%
name 6937
24.8%
english 4485
16.0%
en 4485
16.0%
fr 437
 
1.6%
fran\u00e7ais 437
 
1.6%
es 351
 
1.3%
espa\u00f1ol 351
 
1.3%
deutsch 262
 
0.9%
de 262
 
0.9%
Other values (144) 3010
10.8%
2025-01-08T13:09:22.071386image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 55496
18.4%
23151
 
7.7%
n 16768
 
5.5%
e 13992
 
4.6%
: 13874
 
4.6%
_ 13874
 
4.6%
s 13221
 
4.4%
i 12537
 
4.1%
a 9800
 
3.2%
, 9157
 
3.0%
Other values (58) 120351
39.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 108442
35.9%
Other Punctuation 83645
27.7%
Decimal Number 43345
 
14.3%
Space Separator 23151
 
7.7%
Connector Punctuation 13874
 
4.6%
Close Punctuation 11740
 
3.9%
Open Punctuation 11740
 
3.9%
Uppercase Letter 6284
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 16768
15.5%
e 13992
12.9%
s 13221
12.2%
i 12537
11.6%
a 9800
9.0%
o 7712
7.1%
m 6969
6.4%
u 5701
 
5.3%
l 5259
 
4.8%
h 5047
 
4.7%
Other values (16) 11436
10.5%
Uppercase Letter
ValueCountFrequency (%)
E 4840
77.0%
F 437
 
7.0%
P 306
 
4.9%
D 276
 
4.4%
I 188
 
3.0%
L 54
 
0.9%
M 42
 
0.7%
T 35
 
0.6%
N 25
 
0.4%
V 17
 
0.3%
Other values (10) 64
 
1.0%
Decimal Number
ValueCountFrequency (%)
3 8367
19.3%
1 8142
18.8%
6 8130
18.8%
9 7940
18.3%
0 5276
12.2%
4 2368
 
5.5%
7 872
 
2.0%
5 776
 
1.8%
2 776
 
1.8%
8 698
 
1.6%
Other Punctuation
ValueCountFrequency (%)
" 55496
66.3%
: 13874
 
16.6%
, 9157
 
10.9%
\ 5033
 
6.0%
/ 79
 
0.1%
? 6
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
} 6937
59.1%
] 4803
40.9%
Open Punctuation
ValueCountFrequency (%)
{ 6937
59.1%
[ 4803
40.9%
Space Separator
ValueCountFrequency (%)
23151
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13874
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 187495
62.0%
Latin 114726
38.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 16768
14.6%
e 13992
12.2%
s 13221
11.5%
i 12537
10.9%
a 9800
8.5%
o 7712
6.7%
m 6969
 
6.1%
u 5701
 
5.0%
l 5259
 
4.6%
h 5047
 
4.4%
Other values (36) 17720
15.4%
Common
ValueCountFrequency (%)
" 55496
29.6%
23151
12.3%
: 13874
 
7.4%
_ 13874
 
7.4%
, 9157
 
4.9%
3 8367
 
4.5%
1 8142
 
4.3%
6 8130
 
4.3%
9 7940
 
4.2%
} 6937
 
3.7%
Other values (12) 32427
17.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 302221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 55496
18.4%
23151
 
7.7%
n 16768
 
5.5%
e 13992
 
4.6%
: 13874
 
4.6%
_ 13874
 
4.6%
s 13221
 
4.4%
i 12537
 
4.1%
a 9800
 
3.2%
, 9157
 
3.0%
Other values (58) 120351
39.8%

status
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
Released
4795 
Rumored
 
5
Post Production
 
3

Length

Max length15
Median length8
Mean length8.0033313
Min length7

Characters and Unicode

Total characters38440
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReleased
2nd rowReleased
3rd rowReleased
4th rowReleased
5th rowReleased

Common Values

ValueCountFrequency (%)
Released 4795
99.8%
Rumored 5
 
0.1%
Post Production 3
 
0.1%

Length

2025-01-08T13:09:22.183618image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-08T13:09:22.282329image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
ValueCountFrequency (%)
released 4795
99.8%
rumored 5
 
0.1%
post 3
 
0.1%
production 3
 
0.1%

Most occurring characters

ValueCountFrequency (%)
e 14390
37.4%
d 4803
 
12.5%
R 4800
 
12.5%
s 4798
 
12.5%
l 4795
 
12.5%
a 4795
 
12.5%
o 14
 
< 0.1%
u 8
 
< 0.1%
r 8
 
< 0.1%
P 6
 
< 0.1%
Other values (6) 23
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 33631
87.5%
Uppercase Letter 4806
 
12.5%
Space Separator 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 14390
42.8%
d 4803
 
14.3%
s 4798
 
14.3%
l 4795
 
14.3%
a 4795
 
14.3%
o 14
 
< 0.1%
u 8
 
< 0.1%
r 8
 
< 0.1%
t 6
 
< 0.1%
m 5
 
< 0.1%
Other values (3) 9
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
R 4800
99.9%
P 6
 
0.1%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38437
> 99.9%
Common 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 14390
37.4%
d 4803
 
12.5%
R 4800
 
12.5%
s 4798
 
12.5%
l 4795
 
12.5%
a 4795
 
12.5%
o 14
 
< 0.1%
u 8
 
< 0.1%
r 8
 
< 0.1%
P 6
 
< 0.1%
Other values (5) 20
 
0.1%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 14390
37.4%
d 4803
 
12.5%
R 4800
 
12.5%
s 4798
 
12.5%
l 4795
 
12.5%
a 4795
 
12.5%
o 14
 
< 0.1%
u 8
 
< 0.1%
r 8
 
< 0.1%
P 6
 
< 0.1%
Other values (6) 23
 
0.1%

tagline
Text

MISSING 

Distinct3944
Distinct (%)99.6%
Missing844
Missing (%)17.6%
Memory size37.6 KiB
2025-01-08T13:09:22.555143image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length252
Median length149
Mean length41.988886
Min length3

Characters and Unicode

Total characters166234
Distinct characters92
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3930 ?
Unique (%)99.3%

Sample

1st rowEnter the World of Pandora.
2nd rowAt the end of the world, the adventure begins.
3rd rowA Plan No One Escapes
4th rowThe Legend Ends
5th rowLost in our world, found in another.
ValueCountFrequency (%)
the 1880
 
6.1%
a 1085
 
3.5%
to 705
 
2.3%
is 653
 
2.1%
of 620
 
2.0%
you 535
 
1.7%
in 443
 
1.4%
and 328
 
1.1%
for 323
 
1.0%
it 310
 
1.0%
Other values (4349) 23980
77.7%
2025-01-08T13:09:22.991786image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26926
16.2%
e 17450
 
10.5%
o 10463
 
6.3%
t 10358
 
6.2%
a 8761
 
5.3%
n 8406
 
5.1%
i 8137
 
4.9%
r 7933
 
4.8%
s 7648
 
4.6%
h 6587
 
4.0%
Other values (82) 53565
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 121321
73.0%
Space Separator 26926
 
16.2%
Uppercase Letter 9700
 
5.8%
Other Punctuation 7563
 
4.5%
Decimal Number 521
 
0.3%
Dash Punctuation 150
 
0.1%
Final Punctuation 28
 
< 0.1%
Open Punctuation 8
 
< 0.1%
Close Punctuation 8
 
< 0.1%
Other Letter 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 17450
14.4%
o 10463
 
8.6%
t 10358
 
8.5%
a 8761
 
7.2%
n 8406
 
6.9%
i 8137
 
6.7%
r 7933
 
6.5%
s 7648
 
6.3%
h 6587
 
5.4%
l 5132
 
4.2%
Other values (18) 30446
25.1%
Uppercase Letter
ValueCountFrequency (%)
T 1492
15.4%
A 827
 
8.5%
S 708
 
7.3%
I 599
 
6.2%
W 592
 
6.1%
H 585
 
6.0%
B 478
 
4.9%
N 430
 
4.4%
F 419
 
4.3%
E 411
 
4.2%
Other values (16) 3159
32.6%
Other Punctuation
ValueCountFrequency (%)
. 5147
68.1%
' 1039
 
13.7%
, 725
 
9.6%
! 356
 
4.7%
? 220
 
2.9%
" 20
 
0.3%
: 14
 
0.2%
10
 
0.1%
& 9
 
0.1%
% 9
 
0.1%
Other values (4) 14
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 162
31.1%
1 99
19.0%
2 55
 
10.6%
9 38
 
7.3%
3 37
 
7.1%
7 28
 
5.4%
5 27
 
5.2%
4 26
 
5.0%
6 25
 
4.8%
8 24
 
4.6%
Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 149
99.3%
1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 7
87.5%
[ 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 7
87.5%
] 1
 
12.5%
Space Separator
ValueCountFrequency (%)
26926
100.0%
Final Punctuation
ValueCountFrequency (%)
28
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 131021
78.8%
Common 35208
 
21.2%
Han 5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 17450
13.3%
o 10463
 
8.0%
t 10358
 
7.9%
a 8761
 
6.7%
n 8406
 
6.4%
i 8137
 
6.2%
r 7933
 
6.1%
s 7648
 
5.8%
h 6587
 
5.0%
l 5132
 
3.9%
Other values (44) 40146
30.6%
Common
ValueCountFrequency (%)
26926
76.5%
. 5147
 
14.6%
' 1039
 
3.0%
, 725
 
2.1%
! 356
 
1.0%
? 220
 
0.6%
0 162
 
0.5%
- 149
 
0.4%
1 99
 
0.3%
2 55
 
0.2%
Other values (23) 330
 
0.9%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 166188
> 99.9%
Punctuation 39
 
< 0.1%
CJK 5
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26926
16.2%
e 17450
 
10.5%
o 10463
 
6.3%
t 10358
 
6.2%
a 8761
 
5.3%
n 8406
 
5.1%
i 8137
 
4.9%
r 7933
 
4.8%
s 7648
 
4.6%
h 6587
 
4.0%
Other values (72) 53519
32.2%
Punctuation
ValueCountFrequency (%)
28
71.8%
10
 
25.6%
1
 
2.6%
None
ValueCountFrequency (%)
é 1
50.0%
á 1
50.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

title
Text

Distinct4800
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:23.315553image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length86
Median length58
Mean length15.349157
Min length1

Characters and Unicode

Total characters73722
Distinct characters98
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4797 ?
Unique (%)99.9%

Sample

1st rowAvatar
2nd rowPirates of the Caribbean: At World's End
3rd rowSpectre
4th rowThe Dark Knight Rises
5th rowJohn Carter
ValueCountFrequency (%)
the 1526
 
11.4%
of 474
 
3.5%
a 180
 
1.3%
and 139
 
1.0%
in 116
 
0.9%
to 107
 
0.8%
2 103
 
0.8%
79
 
0.6%
man 66
 
0.5%
love 56
 
0.4%
Other values (4810) 10508
78.7%
2025-01-08T13:09:23.777414image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8553
 
11.6%
e 7525
 
10.2%
a 4632
 
6.3%
o 4470
 
6.1%
n 3950
 
5.4%
r 3946
 
5.4%
i 3765
 
5.1%
t 3660
 
5.0%
s 2862
 
3.9%
h 2852
 
3.9%
Other values (88) 27507
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51907
70.4%
Uppercase Letter 11748
 
15.9%
Space Separator 8553
 
11.6%
Other Punctuation 909
 
1.2%
Decimal Number 494
 
0.7%
Dash Punctuation 82
 
0.1%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Currency Symbol 4
 
< 0.1%
Other Number 4
 
< 0.1%
Other values (4) 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7525
14.5%
a 4632
 
8.9%
o 4470
 
8.6%
n 3950
 
7.6%
r 3946
 
7.6%
i 3765
 
7.3%
t 3660
 
7.1%
s 2862
 
5.5%
h 2852
 
5.5%
l 2417
 
4.7%
Other values (23) 11828
22.8%
Uppercase Letter
ValueCountFrequency (%)
T 1668
14.2%
S 1007
 
8.6%
M 800
 
6.8%
B 756
 
6.4%
D 687
 
5.8%
C 663
 
5.6%
A 640
 
5.4%
L 543
 
4.6%
H 541
 
4.6%
W 500
 
4.3%
Other values (17) 3943
33.6%
Other Punctuation
ValueCountFrequency (%)
: 351
38.6%
' 221
24.3%
. 141
15.5%
, 75
 
8.3%
& 61
 
6.7%
! 31
 
3.4%
? 17
 
1.9%
/ 7
 
0.8%
* 2
 
0.2%
# 2
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 146
29.6%
1 79
16.0%
0 77
15.6%
3 72
14.6%
4 33
 
6.7%
5 21
 
4.3%
8 21
 
4.3%
9 16
 
3.2%
7 15
 
3.0%
6 14
 
2.8%
Other Number
ValueCountFrequency (%)
½ 1
25.0%
³ 1
25.0%
² 1
25.0%
1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
97.6%
2
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 5
71.4%
[ 2
 
28.6%
Close Punctuation
ValueCountFrequency (%)
) 5
71.4%
] 2
 
28.6%
Currency Symbol
ValueCountFrequency (%)
¢ 2
50.0%
$ 2
50.0%
Space Separator
ValueCountFrequency (%)
8553
100.0%
Final Punctuation
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 63655
86.3%
Common 10067
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7525
 
11.8%
a 4632
 
7.3%
o 4470
 
7.0%
n 3950
 
6.2%
r 3946
 
6.2%
i 3765
 
5.9%
t 3660
 
5.7%
s 2862
 
4.5%
h 2852
 
4.5%
l 2417
 
3.8%
Other values (50) 23576
37.0%
Common
ValueCountFrequency (%)
8553
85.0%
: 351
 
3.5%
' 221
 
2.2%
2 146
 
1.5%
. 141
 
1.4%
- 80
 
0.8%
1 79
 
0.8%
0 77
 
0.8%
, 75
 
0.7%
3 72
 
0.7%
Other values (28) 272
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73696
> 99.9%
None 20
 
< 0.1%
Punctuation 5
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8553
 
11.6%
e 7525
 
10.2%
a 4632
 
6.3%
o 4470
 
6.1%
n 3950
 
5.4%
r 3946
 
5.4%
i 3765
 
5.1%
t 3660
 
5.0%
s 2862
 
3.9%
h 2852
 
3.9%
Other values (71) 27481
37.3%
None
ValueCountFrequency (%)
é 6
30.0%
¢ 2
 
10.0%
Æ 1
 
5.0%
ë 1
 
5.0%
½ 1
 
5.0%
à 1
 
5.0%
· 1
 
5.0%
ü 1
 
5.0%
³ 1
 
5.0%
á 1
 
5.0%
Other values (4) 4
20.0%
Punctuation
ValueCountFrequency (%)
3
60.0%
2
40.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

vote_average
Real number (ℝ)

ZEROS 

Distinct71
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0921716
Minimum0
Maximum10
Zeros63
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:23.898813image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.3
Q15.6
median6.2
Q36.8
95-th percentile7.6
Maximum10
Range10
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation1.1946122
Coefficient of variation (CV)0.19608971
Kurtosis7.7923628
Mean6.0921716
Median Absolute Deviation (MAD)0.6
Skewness-1.95971
Sum29260.7
Variance1.4270982
MonotonicityNot monotonic
2025-01-08T13:09:24.006675image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.5 216
 
4.5%
6 216
 
4.5%
6.7 213
 
4.4%
6.3 207
 
4.3%
6.1 201
 
4.2%
6.4 201
 
4.2%
6.2 200
 
4.2%
6.6 198
 
4.1%
5.9 196
 
4.1%
5.8 187
 
3.9%
Other values (61) 2768
57.6%
ValueCountFrequency (%)
0 63
1.3%
0.5 1
 
< 0.1%
1 2
 
< 0.1%
1.9 1
 
< 0.1%
2 6
 
0.1%
2.2 1
 
< 0.1%
2.3 2
 
< 0.1%
2.4 1
 
< 0.1%
2.6 1
 
< 0.1%
2.7 1
 
< 0.1%
ValueCountFrequency (%)
10 4
 
0.1%
9.5 1
 
< 0.1%
9.3 1
 
< 0.1%
8.5 2
 
< 0.1%
8.4 2
 
< 0.1%
8.3 7
 
0.1%
8.2 15
0.3%
8.1 18
0.4%
8 35
0.7%
7.9 32
0.7%

vote_count
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1609
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean690.21799
Minimum0
Maximum13752
Zeros62
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2025-01-08T13:09:24.130682image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q154
median235
Q3737
95-th percentile3040.9
Maximum13752
Range13752
Interquartile range (IQR)683

Descriptive statistics

Standard deviation1234.5859
Coefficient of variation (CV)1.7886898
Kurtosis19.913946
Mean690.21799
Median Absolute Deviation (MAD)214
Skewness3.8240685
Sum3315117
Variance1524202.3
MonotonicityNot monotonic
2025-01-08T13:09:24.275671image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 62
 
1.3%
1 53
 
1.1%
2 46
 
1.0%
4 43
 
0.9%
3 41
 
0.9%
6 38
 
0.8%
8 37
 
0.8%
10 34
 
0.7%
11 32
 
0.7%
9 32
 
0.7%
Other values (1599) 4385
91.3%
ValueCountFrequency (%)
0 62
1.3%
1 53
1.1%
2 46
1.0%
3 41
0.9%
4 43
0.9%
5 28
0.6%
6 38
0.8%
7 31
0.6%
8 37
0.8%
9 32
0.7%
ValueCountFrequency (%)
13752 1
< 0.1%
12002 1
< 0.1%
11800 1
< 0.1%
11776 1
< 0.1%
10995 1
< 0.1%
10867 1
< 0.1%
10099 1
< 0.1%
9742 1
< 0.1%
9455 1
< 0.1%
9427 1
< 0.1%

Interactions

2025-01-08T13:09:13.512841image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:09.381236image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.118169image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.778986image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:11.444453image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:12.141234image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:12.848524image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:13.619197image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:09.489116image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.219454image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.880953image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:11.550987image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:12.248942image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:12.949487image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:13.713766image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:09.584481image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.306291image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.971997image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:11.644154image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:12.345682image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:13.039070image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:13.808066image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:09.679077image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.393726image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:11.059088image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:11.738209image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:12.441412image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:13.128183image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:13.907980image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:09.780506image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.485538image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:11.154102image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:11.835583image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:12.543671image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:13.221984image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:14.011374image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:09.911436image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.585945image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:11.251400image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:11.939129image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:12.648335image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:13.321052image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:14.431338image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.011441image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:10.679413image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:11.343907image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:12.036458image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:12.745422image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2025-01-08T13:09:13.412903image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2025-01-08T13:09:24.391902image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
budgetidpopularityrevenueruntimevote_averagevote_countoriginal_languagestatus
budget1.000-0.2460.6490.7570.3260.0660.6630.0000.000
id-0.2461.000-0.278-0.292-0.216-0.266-0.2970.0890.048
popularity0.649-0.2781.0000.7770.3020.3590.9600.0000.000
revenue0.757-0.2920.7771.0000.3170.2430.8040.0000.000
runtime0.326-0.2160.3020.3171.0000.3980.3040.0200.029
vote_average0.066-0.2660.3590.2430.3981.0000.3810.0590.131
vote_count0.663-0.2970.9600.8040.3040.3811.0000.0000.000
original_language0.0000.0890.0000.0000.0200.0590.0001.0000.275
status0.0000.0480.0000.0000.0290.1310.0000.2751.000

Missing values

2025-01-08T13:09:14.617672image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
A simple visualization of nullity by column.
2025-01-08T13:09:14.956172image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-01-08T13:09:15.189043image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

budgetgenreshomepageidkeywordsoriginal_languageoriginal_titleoverviewpopularityproduction_companiesproduction_countriesrelease_daterevenueruntimespoken_languagesstatustaglinetitlevote_averagevote_count
0237000000[{"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}, {"id": 14, "name": "Fantasy"}, {"id": 878, "name": "Science Fiction"}]http://www.avatarmovie.com/19995[{"id": 1463, "name": "culture clash"}, {"id": 2964, "name": "future"}, {"id": 3386, "name": "space war"}, {"id": 3388, "name": "space colony"}, {"id": 3679, "name": "society"}, {"id": 3801, "name": "space travel"}, {"id": 9685, "name": "futuristic"}, {"id": 9840, "name": "romance"}, {"id": 9882, "name": "space"}, {"id": 9951, "name": "alien"}, {"id": 10148, "name": "tribe"}, {"id": 10158, "name": "alien planet"}, {"id": 10987, "name": "cgi"}, {"id": 11399, "name": "marine"}, {"id": 13065, "name": "soldier"}, {"id": 14643, "name": "battle"}, {"id": 14720, "name": "love affair"}, {"id": 165431, "name": "anti war"}, {"id": 193554, "name": "power relations"}, {"id": 206690, "name": "mind and soul"}, {"id": 209714, "name": "3d"}]enAvatarIn the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.150.437577[{"name": "Ingenious Film Partners", "id": 289}, {"name": "Twentieth Century Fox Film Corporation", "id": 306}, {"name": "Dune Entertainment", "id": 444}, {"name": "Lightstorm Entertainment", "id": 574}][{"iso_3166_1": "US", "name": "United States of America"}, {"iso_3166_1": "GB", "name": "United Kingdom"}]2009-12-102787965087162.0[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "es", "name": "Espa\u00f1ol"}]ReleasedEnter the World of Pandora.Avatar7.211800
1300000000[{"id": 12, "name": "Adventure"}, {"id": 14, "name": "Fantasy"}, {"id": 28, "name": "Action"}]http://disney.go.com/disneypictures/pirates/285[{"id": 270, "name": "ocean"}, {"id": 726, "name": "drug abuse"}, {"id": 911, "name": "exotic island"}, {"id": 1319, "name": "east india trading company"}, {"id": 2038, "name": "love of one's life"}, {"id": 2052, "name": "traitor"}, {"id": 2580, "name": "shipwreck"}, {"id": 2660, "name": "strong woman"}, {"id": 3799, "name": "ship"}, {"id": 5740, "name": "alliance"}, {"id": 5941, "name": "calypso"}, {"id": 6155, "name": "afterlife"}, {"id": 6211, "name": "fighter"}, {"id": 12988, "name": "pirate"}, {"id": 157186, "name": "swashbuckler"}, {"id": 179430, "name": "aftercreditsstinger"}]enPirates of the Caribbean: At World's EndCaptain Barbossa, long believed to be dead, has come back to life and is headed to the edge of the Earth with Will Turner and Elizabeth Swann. But nothing is quite as it seems.139.082615[{"name": "Walt Disney Pictures", "id": 2}, {"name": "Jerry Bruckheimer Films", "id": 130}, {"name": "Second Mate Productions", "id": 19936}][{"iso_3166_1": "US", "name": "United States of America"}]2007-05-19961000000169.0[{"iso_639_1": "en", "name": "English"}]ReleasedAt the end of the world, the adventure begins.Pirates of the Caribbean: At World's End6.94500
2245000000[{"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}, {"id": 80, "name": "Crime"}]http://www.sonypictures.com/movies/spectre/206647[{"id": 470, "name": "spy"}, {"id": 818, "name": "based on novel"}, {"id": 4289, "name": "secret agent"}, {"id": 9663, "name": "sequel"}, {"id": 14555, "name": "mi6"}, {"id": 156095, "name": "british secret service"}, {"id": 158431, "name": "united kingdom"}]enSpectreA cryptic message from Bond’s past sends him on a trail to uncover a sinister organization. While M battles political forces to keep the secret service alive, Bond peels back the layers of deceit to reveal the terrible truth behind SPECTRE.107.376788[{"name": "Columbia Pictures", "id": 5}, {"name": "Danjaq", "id": 10761}, {"name": "B24", "id": 69434}][{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]2015-10-26880674609148.0[{"iso_639_1": "fr", "name": "Fran\u00e7ais"}, {"iso_639_1": "en", "name": "English"}, {"iso_639_1": "es", "name": "Espa\u00f1ol"}, {"iso_639_1": "it", "name": "Italiano"}, {"iso_639_1": "de", "name": "Deutsch"}]ReleasedA Plan No One EscapesSpectre6.34466
3250000000[{"id": 28, "name": "Action"}, {"id": 80, "name": "Crime"}, {"id": 18, "name": "Drama"}, {"id": 53, "name": "Thriller"}]http://www.thedarkknightrises.com/49026[{"id": 849, "name": "dc comics"}, {"id": 853, "name": "crime fighter"}, {"id": 949, "name": "terrorist"}, {"id": 1308, "name": "secret identity"}, {"id": 1437, "name": "burglar"}, {"id": 3051, "name": "hostage drama"}, {"id": 3562, "name": "time bomb"}, {"id": 6969, "name": "gotham city"}, {"id": 7002, "name": "vigilante"}, {"id": 9665, "name": "cover-up"}, {"id": 9715, "name": "superhero"}, {"id": 9990, "name": "villainess"}, {"id": 10044, "name": "tragic hero"}, {"id": 13015, "name": "terrorism"}, {"id": 14796, "name": "destruction"}, {"id": 18933, "name": "catwoman"}, {"id": 156082, "name": "cat burglar"}, {"id": 156395, "name": "imax"}, {"id": 173272, "name": "flood"}, {"id": 179093, "name": "criminal underworld"}, {"id": 230775, "name": "batman"}]enThe Dark Knight RisesFollowing the death of District Attorney Harvey Dent, Batman assumes responsibility for Dent's crimes to protect the late attorney's reputation and is subsequently hunted by the Gotham City Police Department. Eight years later, Batman encounters the mysterious Selina Kyle and the villainous Bane, a new terrorist leader who overwhelms Gotham's finest. The Dark Knight resurfaces to protect a city that has branded him an enemy.112.312950[{"name": "Legendary Pictures", "id": 923}, {"name": "Warner Bros.", "id": 6194}, {"name": "DC Entertainment", "id": 9993}, {"name": "Syncopy", "id": 9996}][{"iso_3166_1": "US", "name": "United States of America"}]2012-07-161084939099165.0[{"iso_639_1": "en", "name": "English"}]ReleasedThe Legend EndsThe Dark Knight Rises7.69106
4260000000[{"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}, {"id": 878, "name": "Science Fiction"}]http://movies.disney.com/john-carter49529[{"id": 818, "name": "based on novel"}, {"id": 839, "name": "mars"}, {"id": 1456, "name": "medallion"}, {"id": 3801, "name": "space travel"}, {"id": 7376, "name": "princess"}, {"id": 9951, "name": "alien"}, {"id": 10028, "name": "steampunk"}, {"id": 10539, "name": "martian"}, {"id": 10685, "name": "escape"}, {"id": 161511, "name": "edgar rice burroughs"}, {"id": 163252, "name": "alien race"}, {"id": 179102, "name": "superhuman strength"}, {"id": 190320, "name": "mars civilization"}, {"id": 195446, "name": "sword and planet"}, {"id": 207928, "name": "19th century"}, {"id": 209714, "name": "3d"}]enJohn CarterJohn Carter is a war-weary, former military captain who's inexplicably transported to the mysterious and exotic planet of Barsoom (Mars) and reluctantly becomes embroiled in an epic conflict. It's a world on the brink of collapse, and Carter rediscovers his humanity when he realizes the survival of Barsoom and its people rests in his hands.43.926995[{"name": "Walt Disney Pictures", "id": 2}][{"iso_3166_1": "US", "name": "United States of America"}]2012-03-07284139100132.0[{"iso_639_1": "en", "name": "English"}]ReleasedLost in our world, found in another.John Carter6.12124
5258000000[{"id": 14, "name": "Fantasy"}, {"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}]http://www.sonypictures.com/movies/spider-man3/559[{"id": 851, "name": "dual identity"}, {"id": 1453, "name": "amnesia"}, {"id": 1965, "name": "sandstorm"}, {"id": 2038, "name": "love of one's life"}, {"id": 3446, "name": "forgiveness"}, {"id": 3986, "name": "spider"}, {"id": 4391, "name": "wretch"}, {"id": 4959, "name": "death of a friend"}, {"id": 5776, "name": "egomania"}, {"id": 5789, "name": "sand"}, {"id": 5857, "name": "narcism"}, {"id": 6062, "name": "hostility"}, {"id": 8828, "name": "marvel comic"}, {"id": 9663, "name": "sequel"}, {"id": 9715, "name": "superhero"}, {"id": 9748, "name": "revenge"}]enSpider-Man 3The seemingly invincible Spider-Man goes up against an all-new crop of villain – including the shape-shifting Sandman. While Spider-Man’s superpowers are altered by an alien organism, his alter ego, Peter Parker, deals with nemesis Eddie Brock and also gets caught up in a love triangle.115.699814[{"name": "Columbia Pictures", "id": 5}, {"name": "Laura Ziskin Productions", "id": 326}, {"name": "Marvel Enterprises", "id": 19551}][{"iso_3166_1": "US", "name": "United States of America"}]2007-05-01890871626139.0[{"iso_639_1": "en", "name": "English"}, {"iso_639_1": "fr", "name": "Fran\u00e7ais"}]ReleasedThe battle within.Spider-Man 35.93576
6260000000[{"id": 16, "name": "Animation"}, {"id": 10751, "name": "Family"}]http://disney.go.com/disneypictures/tangled/38757[{"id": 1562, "name": "hostage"}, {"id": 2343, "name": "magic"}, {"id": 2673, "name": "horse"}, {"id": 3205, "name": "fairy tale"}, {"id": 4344, "name": "musical"}, {"id": 7376, "name": "princess"}, {"id": 10336, "name": "animation"}, {"id": 33787, "name": "tower"}, {"id": 155658, "name": "blonde woman"}, {"id": 162219, "name": "selfishness"}, {"id": 163545, "name": "healing power"}, {"id": 179411, "name": "based on fairy tale"}, {"id": 179431, "name": "duringcreditsstinger"}, {"id": 215258, "name": "healing gift"}, {"id": 234183, "name": "animal sidekick"}]enTangledWhen the kingdom's most wanted-and most charming-bandit Flynn Rider hides out in a mysterious tower, he's taken hostage by Rapunzel, a beautiful and feisty tower-bound teen with 70 feet of magical, golden hair. Flynn's curious captor, who's looking for her ticket out of the tower where she's been locked away for years, strikes a deal with the handsome thief and the unlikely duo sets off on an action-packed escapade, complete with a super-cop horse, an over-protective chameleon and a gruff gang of pub thugs.48.681969[{"name": "Walt Disney Pictures", "id": 2}, {"name": "Walt Disney Animation Studios", "id": 6125}][{"iso_3166_1": "US", "name": "United States of America"}]2010-11-24591794936100.0[{"iso_639_1": "en", "name": "English"}]ReleasedThey're taking adventure to new lengths.Tangled7.43330
7280000000[{"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}, {"id": 878, "name": "Science Fiction"}]http://marvel.com/movies/movie/193/avengers_age_of_ultron99861[{"id": 8828, "name": "marvel comic"}, {"id": 9663, "name": "sequel"}, {"id": 9715, "name": "superhero"}, {"id": 9717, "name": "based on comic book"}, {"id": 10629, "name": "vision"}, {"id": 155030, "name": "superhero team"}, {"id": 179431, "name": "duringcreditsstinger"}, {"id": 180547, "name": "marvel cinematic universe"}, {"id": 209714, "name": "3d"}]enAvengers: Age of UltronWhen Tony Stark tries to jumpstart a dormant peacekeeping program, things go awry and Earth’s Mightiest Heroes are put to the ultimate test as the fate of the planet hangs in the balance. As the villainous Ultron emerges, it is up to The Avengers to stop him from enacting his terrible plans, and soon uneasy alliances and unexpected action pave the way for an epic and unique global adventure.134.279229[{"name": "Marvel Studios", "id": 420}, {"name": "Prime Focus", "id": 15357}, {"name": "Revolution Sun Studios", "id": 76043}][{"iso_3166_1": "US", "name": "United States of America"}]2015-04-221405403694141.0[{"iso_639_1": "en", "name": "English"}]ReleasedA New Age Has Come.Avengers: Age of Ultron7.36767
8250000000[{"id": 12, "name": "Adventure"}, {"id": 14, "name": "Fantasy"}, {"id": 10751, "name": "Family"}]http://harrypotter.warnerbros.com/harrypotterandthehalf-bloodprince/dvd/index.html767[{"id": 616, "name": "witch"}, {"id": 2343, "name": "magic"}, {"id": 3872, "name": "broom"}, {"id": 3884, "name": "school of witchcraft"}, {"id": 6333, "name": "wizardry"}, {"id": 10164, "name": "apparition"}, {"id": 10791, "name": "teenage crush"}, {"id": 12564, "name": "werewolf"}]enHarry Potter and the Half-Blood PrinceAs Harry begins his sixth year at Hogwarts, he discovers an old book marked as 'Property of the Half-Blood Prince', and begins to learn more about Lord Voldemort's dark past.98.885637[{"name": "Warner Bros.", "id": 6194}, {"name": "Heyday Films", "id": 7364}][{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]2009-07-07933959197153.0[{"iso_639_1": "en", "name": "English"}]ReleasedDark Secrets RevealedHarry Potter and the Half-Blood Prince7.45293
9250000000[{"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}, {"id": 14, "name": "Fantasy"}]http://www.batmanvsupermandawnofjustice.com/209112[{"id": 849, "name": "dc comics"}, {"id": 7002, "name": "vigilante"}, {"id": 9715, "name": "superhero"}, {"id": 9717, "name": "based on comic book"}, {"id": 9748, "name": "revenge"}, {"id": 163455, "name": "super powers"}, {"id": 195242, "name": "clark kent"}, {"id": 195243, "name": "bruce wayne"}, {"id": 229266, "name": "dc extended universe"}]enBatman v Superman: Dawn of JusticeFearing the actions of a god-like Super Hero left unchecked, Gotham City’s own formidable, forceful vigilante takes on Metropolis’s most revered, modern-day savior, while the world wrestles with what sort of hero it really needs. And with Batman and Superman at war with one another, a new threat quickly arises, putting mankind in greater danger than it’s ever known before.155.790452[{"name": "DC Comics", "id": 429}, {"name": "Atlas Entertainment", "id": 507}, {"name": "Warner Bros.", "id": 6194}, {"name": "DC Entertainment", "id": 9993}, {"name": "Cruel & Unusual Films", "id": 9995}, {"name": "RatPac-Dune Entertainment", "id": 41624}][{"iso_3166_1": "US", "name": "United States of America"}]2016-03-23873260194151.0[{"iso_639_1": "en", "name": "English"}]ReleasedJustice or revengeBatman v Superman: Dawn of Justice5.77004
budgetgenreshomepageidkeywordsoriginal_languageoriginal_titleoverviewpopularityproduction_companiesproduction_countriesrelease_daterevenueruntimespoken_languagesstatustaglinetitlevote_averagevote_count
47930[{"id": 18, "name": "Drama"}]NaN182291[{"id": 718, "name": "confession"}, {"id": 10079, "name": "hazing"}, {"id": 33426, "name": "gang member"}, {"id": 33586, "name": "latino"}, {"id": 158718, "name": "lgbt"}, {"id": 172391, "name": "catholic priest"}, {"id": 196374, "name": "shakespeare's romeo and juliet"}, {"id": 208340, "name": "latino lgbt"}, {"id": 209241, "name": "gang initiation"}, {"id": 209242, "name": "gunplay"}]enOn The DownlowIsaac and Angel are two young Latinos involved in a south side Chicago gang. They have a secret in a world where secrets are forbidden.0.029757[{"name": "Iconoclast Films", "id": 26677}][{"iso_3166_1": "US", "name": "United States of America"}]2004-04-11090.0[]ReleasedTwo gangs. One secret. One crossroad.On The Downlow6.02
47940[{"id": 53, "name": "Thriller"}, {"id": 27, "name": "Horror"}, {"id": 35, "name": "Comedy"}]NaN286939[]enSanctuary: Quite a ConundrumIt should have been just a normal day of sex, fun, alcohol, hormones and debauchery for Tabitha and Mimi, two over-privileged twenty-somethings. But that so-called normalcy gets tossed out the window when a devastating event occurs at a pool party.0.166513[{"name": "Gold Lion Films", "id": 37870}, {"name": "T-Street Productions", "id": 37871}][{"iso_3166_1": "US", "name": "United States of America"}]2012-01-20082.0[{"iso_639_1": "en", "name": "English"}]ReleasedNaNSanctuary: Quite a Conundrum0.00
47950[{"id": 18, "name": "Drama"}]NaN124606[{"id": 10726, "name": "gang"}, {"id": 33928, "name": "audition"}, {"id": 172732, "name": "police fake"}, {"id": 177927, "name": "homeless"}, {"id": 207583, "name": "actress"}]enBangA young woman in L.A. is having a bad day: she's evicted, an audition ends with a producer furious she won't trade sex for the part, and a policeman nabs her for something she didn't do, demanding fellatio to release her. She snaps, grabs his gun, takes his uniform, and leaves him cuffed to a tree where he's soon having a defenseless chat with a homeless man. She takes off on the cop's motorcycle and, for an afternoon, experiences a cop's life. She talks a young man out of suicide and then is plunged into violence after a friendly encounter with two "vatos." She is torn between self-protection and others' expectations. Is there any resolution for her torrent of feelings?0.918116[{"name": "Asylum Films", "id": 10571}, {"name": "FM Entertainment", "id": 26598}, {"name": "Eagle Eye Films Inc.", "id": 40739}][{"iso_3166_1": "US", "name": "United States of America"}]1995-09-09098.0[{"iso_639_1": "en", "name": "English"}]ReleasedSometimes you've got to break the rulesBang6.01
47967000[{"id": 878, "name": "Science Fiction"}, {"id": 18, "name": "Drama"}, {"id": 53, "name": "Thriller"}]http://www.primermovie.com14337[{"id": 1448, "name": "distrust"}, {"id": 2101, "name": "garage"}, {"id": 3394, "name": "identity crisis"}, {"id": 4379, "name": "time travel"}, {"id": 5455, "name": "time machine"}, {"id": 6009, "name": "mathematics"}, {"id": 10183, "name": "independent film"}, {"id": 14779, "name": "paradox"}, {"id": 162356, "name": "mechanical engineering"}]enPrimerFriends/fledgling entrepreneurs invent a device in their garage that reduces the apparent mass of any object placed inside it, but they accidentally discover that it has some highly unexpected capabilities -- ones that could enable them to do and to have seemingly anything they want. Taking advantage of this unique opportunity is the first challenge they face. Dealing with the consequences is the next.23.307949[{"name": "Thinkfilm", "id": 446}][{"iso_3166_1": "US", "name": "United States of America"}]2004-10-0842476077.0[{"iso_639_1": "en", "name": "English"}]ReleasedWhat happens if it actually works?Primer6.9658
47970[{"id": 10769, "name": "Foreign"}, {"id": 53, "name": "Thriller"}]NaN67238[]enCaviteAdam, a security guard, travels from California to the Philippines, his native land, for his father's funeral. He arrives in Manila. As he waits, a phone rings in his backpack; he answers it, and a male voice tells him that his mother and sister are captives and will be killed if Adam doesn't cooperate. Over the next hour, the voice sends Adam by bus, taxi, motorized tricycle, and on foot through an urban landscape of busy streets, cramped apartments, a fetid squatters' camp, a bank, a cockfighting arena, and a church. Adam's conversations with the voice cover murder, Islam, jihad, rebellion in Mindanao, and his family. What is it Adam will be commanded to do?0.022173[][]2005-03-12080.0[]ReleasedNaNCavite7.52
4798220000[{"id": 28, "name": "Action"}, {"id": 80, "name": "Crime"}, {"id": 53, "name": "Thriller"}]NaN9367[{"id": 5616, "name": "united states\u2013mexico barrier"}, {"id": 33649, "name": "legs"}, {"id": 162740, "name": "arms"}, {"id": 187891, "name": "paper knife"}, {"id": 206558, "name": "guitar case"}]esEl MariachiEl Mariachi just wants to play his guitar and carry on the family tradition. Unfortunately, the town he tries to find work in has another visitor...a killer who carries his guns in a guitar case. The drug lord and his henchmen mistake El Mariachi for the killer, Azul, and chase him around town trying to kill him and get his guitar case.14.269792[{"name": "Columbia Pictures", "id": 5}][{"iso_3166_1": "MX", "name": "Mexico"}, {"iso_3166_1": "US", "name": "United States of America"}]1992-09-04204092081.0[{"iso_639_1": "es", "name": "Espa\u00f1ol"}]ReleasedHe didn't come looking for trouble, but trouble came looking for him.El Mariachi6.6238
47999000[{"id": 35, "name": "Comedy"}, {"id": 10749, "name": "Romance"}]NaN72766[]enNewlywedsA newlywed couple's honeymoon is upended by the arrivals of their respective sisters.0.642552[][]2011-12-26085.0[]ReleasedA newlywed couple's honeymoon is upended by the arrivals of their respective sisters.Newlyweds5.95
48000[{"id": 35, "name": "Comedy"}, {"id": 18, "name": "Drama"}, {"id": 10749, "name": "Romance"}, {"id": 10770, "name": "TV Movie"}]http://www.hallmarkchannel.com/signedsealeddelivered231617[{"id": 248, "name": "date"}, {"id": 699, "name": "love at first sight"}, {"id": 2398, "name": "narration"}, {"id": 5340, "name": "investigation"}, {"id": 34051, "name": "team"}, {"id": 173066, "name": "postal worker"}]enSigned, Sealed, Delivered"Signed, Sealed, Delivered" introduces a dedicated quartet of civil servants in the Dead Letter Office of the U.S. Postal System who transform themselves into an elite team of lost-mail detectives. Their determination to deliver the seemingly undeliverable takes them out of the post office into an unpredictable world where letters and packages from the past save lives, solve crimes, reunite old loves, and change futures by arriving late, but always miraculously on time.1.444476[{"name": "Front Street Pictures", "id": 3958}, {"name": "Muse Entertainment Enterprises", "id": 6438}][{"iso_3166_1": "US", "name": "United States of America"}]2013-10-130120.0[{"iso_639_1": "en", "name": "English"}]ReleasedNaNSigned, Sealed, Delivered7.06
48010[]http://shanghaicalling.com/126186[]enShanghai CallingWhen ambitious New York attorney Sam is sent to Shanghai on assignment, he immediately stumbles into a legal mess that could end his career. With the help of a beautiful relocation specialist, a well-connected old-timer, a clever journalist, and a street-smart legal assistant, Sam might just save his job, find romance, and learn to appreciate the beauty and wonders of Shanghai. Written by Anonymous (IMDB.com).0.857008[][{"iso_3166_1": "US", "name": "United States of America"}, {"iso_3166_1": "CN", "name": "China"}]2012-05-03098.0[{"iso_639_1": "en", "name": "English"}]ReleasedA New Yorker in ShanghaiShanghai Calling5.77
48020[{"id": 99, "name": "Documentary"}]NaN25975[{"id": 1523, "name": "obsession"}, {"id": 2249, "name": "camcorder"}, {"id": 9986, "name": "crush"}, {"id": 11223, "name": "dream girl"}]enMy Date with DrewEver since the second grade when he first saw her in E.T. The Extraterrestrial, Brian Herzlinger has had a crush on Drew Barrymore. Now, 20 years later he's decided to try to fulfill his lifelong dream by asking her for a date. There's one small problem: She's Drew Barrymore and he's, well, Brian Herzlinger, a broke 27-year-old aspiring filmmaker from New Jersey.1.929883[{"name": "rusty bear entertainment", "id": 87986}, {"name": "lucky crow films", "id": 87987}][{"iso_3166_1": "US", "name": "United States of America"}]2005-08-05090.0[{"iso_639_1": "en", "name": "English"}]ReleasedNaNMy Date with Drew6.316